Homepage | MoSIS Lab @ UTK
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Zhuohang is presenting the paper at ACM HotMobile 2020.

Mar., 2020

Zhuohang received "ONE-TIME" UTK EECS Fellowship Award! Congratulations!

Feb., 2020
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One paper has been accepted to ICASSP 2020.

In this paper, we propose the first real-time, universal, and robust adversarial attack against the state-of-the-art deep neural network (DNN) based speaker recognition system. Through adding an audio-agnostic universal perturbation on arbitrary enrolled speaker's voice input, the DNN-based speaker recognition system would identify the speaker as any targeted (i.e., adversary-desired) speaker label.

Jan., 2020
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One paper has been accepted to IEEE Transactions on Mobile Computing (IEEE TMC).

We propose the first low-cost sign language gesture recognition system that can differentiate fine-grained finger movements using the Photoplethysmography (PPG) and motion sensors in commodity wearables.

Dec., 2019
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Our work Practical Adversarial Attacks Against Speaker Recognition Systems has been accepted to ACM HotMobile 2020.

In this paper, we propose a practical adversarial attack against the state-of-the-art speaker recognition system. By adding a well-crafted inconspicuous noise to the original audio, our attack can fool the speaker recognition system to make false predictions and even force the audio to be recognized as any adversary-desired speaker. Moreover, our attack integrates the estimated room impulse response (RIR) into the adversarial example training process toward practical audio adversarial examples which could remain effective while being played over the air in the physical world (Led by Zhuohang).

Dec., 2019
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Three papers have been accepted to IEEE INFOCOM'20 .

The three papers are about using PPG sensor, mm-Wave or WiFi signals to capture human's unique behavioral and physiological characteristics (e.g., respiratory, heartbeat, and gait patterns) for continuous user authentication.

Dec., 2019
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Yi is presenting the paper at IEEE DySPAN'19.

Nov., 2019
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Our work Defeating Hidden Audio Channel Attacks on Voice Assistants via Audio-Induced Surface Vibrations has been accepted to ACSAC'19.

In this work, we show that hidden voice commands that mimic the voice features of normal commands, while remaining incomprehensible to humans, can be detected by comparing their speech features in the vibration domain with a sufficient degree of accuracy.

Aug., 2019
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Our work Semi-black-box Attacks Against Speech Recognition Systems Using Adversarial Samples has been accepted to IEEE DySPAN'19.

In this paper, we propose a semi-black-box adversary attack that can embed malicious voice commands into audio clips, and these embedded commands can be recognized by the ASR system Kaldi while remaining unnoticeable to humans (Led by Yi).

Aug., 2019
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Yi joins the MoSIS lab. Welcome!

Aug., 2019
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Zhuohang joins the MoSIS lab. Welcome!

Aug., 2019
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MoSIS Lab website is up!

MoSIS Lab website is up!

Aug., 2019